November 27-December 1st 2023
IAP, Paris / Flatiron institute, New York
Scientific rationale
The 2023 conference on Machine Learning in astronomical surveys intend to critically review new techniques in the Machine Learning methods for astronomy.
In order to bring together the widest possible community, while limiting the carbon impact, this conference will be organized in hybrid mode and on two physical sites simultaneously, at the IAP in Paris and at the CCA/Flatiron Institute in New York. The workshop will take place from Monday to Friday in the afternoon only during hours compatible with both time zones.
Invited reviewers and panellists
Our final list of invited scholars is still evolving beyond the confirm list here-in-below.
Reviewers (confirmed):
In person IAP (Paris):
- Jens Jasche (Stockholm University): ML and Bayesian inference in cosmology
- Tomasz Kacprzak (ETH Zurich): ML and galaxy surveys relevé de galaxies
- Marylou Gabrié (CMAP, Polytechnique): Adaptive techniques for Monte Carlo and generative models
- Miles Cranmer (Cambridge University): Symbolic regression
In person CCA (New York) :
- Soledad Villar (JHU): Symmetries in deep learning
- Tiziana DiMatteo (CMU): Deep learning and numerical simulations
Invited debaters (confirmed):
- Nabila Aghanim (IAS, Orsay)
- Pierre Casenove (CNES)
- Kyunghyun Cho (NYU)
- Aleksandra Ciprijanovic (Fermilab)
- Helena Domínguez Sánchez (CEFCA)
- Torsten Ensslin (MPA)
- David Hogg (NYU / Flatiron Institute)
- François Lanusse (LCS, CNRS)
- Luisa Lucie-Smith (MPA)
- Henry Joy McCracken (IAP, CNRS)
- Licia Verde (ICC-UB)
- David Spergel (Simons Foundation)
- Lawrence Saul (Flatiron Institute)